Results for “xtquant”

Access 31 pay-per-use tools for quantum security, agent safety, research, data, and earn on Base, paid via x402 protocol.

Develops and backtests quantitative trading strategies for the Chinese securities market using the QMT terminal's built-in Python framework, covering data retrieval, order placement, and position management.

Integrate Xquik into apps, scripts, data pipelines, or AI agents for X API tasks like tweet search, user lookup, follower export, media actions, and webhook verification.

Quantize large language models to 8/4/3/2/1-bit precision without calibration data, using multiple optimized backends for deployment with vLLM or HuggingFace Transformers.

Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.

Quantize large language models to 8/4/3/2/1-bit precision without calibration data, using multiple optimized backends and integrations with HuggingFace Transformers, vLLM, and PEFT/LoRA.

Simulações e análise de mecânica quântica usando QuTiP (Quantum Toolbox in Python). Use quando trabalhar com sistemas quânticos incluindo: (1) estados quânticos (kets, bras, matrizes densidade), (2) operadores e gates quânticos, (3) evolução temporal e dinâmica (Schrödinger, equações mestras, Monte Carlo), (4) sistemas quânticos abertos com dissipação, (5) medições quânticas e emaranhamento, (6) visualização (esfera de Bloch, funções de Wigner), (7) estados estacionários e funções de correlação, ou (8) métodos avançados (teoria de Floquet, HEOM, resolutores estocásticos). Manipula sistemas quânticos fechados e abertos em vários domínios incluindo óptica quântica, computação quântica e física da matéria condensada.

Search, analyze, and monitor X/Twitter from the terminal, with support for bookmarks, likes, following, trends, and AI-powered analysis via Grok.

Research Guardian - Ethics Advisory & Bias Detection across all research stages Enhanced VS 3-Phase process: Surface-level screening, deep contextual analysis, constructive recommendations Use when: reviewing research ethics, checking for bias, assessing trustworthiness, QRP screening Triggers: ethics review, IRB, bias detection, QRP, trustworthiness, research integrity, p-hacking, HARKing

Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.

Quantize LLMs to 8/4/3/2/1-bit precision without calibration data, using multiple backends and HuggingFace/vLLM integration.

Search, analyze, and engage with X/Twitter from the terminal, including bookmarks, likes, following, trends, and Grok AI analysis, with export to JSON, CSV, or Markdown.

Quantum computing framework for building, simulating, optimizing, and executing quantum circuits. Use this skill when working with quantum algorithms, quantum circuit design, quantum simulation (noiseless or noisy), running on quantum hardware (Google, IonQ, AQT, Pasqal), circuit optimization and compilation, noise modeling and characterization, or quantum experiments and benchmarking (VQE, QAOA, QPE, randomized benchmarking).

Xquik X data automation API - Use REST or MCP for tweet search, user lookup, follower exports, media downloads, monitors, webhooks, giveaway draws, and confirmation-gated X actions.

Kit de ferramentas abrangente de computação quântica para construir, otimizar e executar circuitos quânticos. Use quando trabalhar com algoritmos quânticos, simulações ou hardware quântico, incluindo (1) Construção de circuitos quânticos com portas e medições, (2) Execução de algoritmos quânticos (VQE, QAOA, Grover), (3) Transpilar/otimizar circuitos para hardware, (4) Executar em IBM Quantum ou outros provedores, (5) Química quântica e ciência dos materiais, (6) Aprendizado de máquina quântico, (7) Visualizar circuitos e resultados, ou (8) Qualquer tarefa de desenvolvimento de computação quântica.

Expert en informatique quantique avancée (Qiskit, Cirq, algorithms, error correction, DZ research)

量化交易核心skill套件 — 因子挖掘、Alpha衰减监控、多市场套利、订单路由、压力测试、归因分析、仓位管理、样本外验证、A股T0、加密资金费率套利、Polymarket机器人。对标国际顶级量化基金（Renaissance/Two Sigma/Citadel/DE Shaw）的工程与策略水平。

Quantum mechanics simulations and analysis using QuTiP (Quantum Toolbox in Python). Use when working with quantum systems including: (1) quantum states (kets, bras, density matrices), (2) quantum operators and gates, (3) time evolution and dynamics (Schrödinger, master equations, Monte Carlo), (4) open quantum systems with dissipation, (5) quantum measurements and entanglement, (6) visualization (Bloch sphere, Wigner functions), (7) steady states and correlation functions, or (8) advanced methods (Floquet theory, HEOM, stochastic solvers). Handles both closed and open quantum systems across various domains including quantum optics, quantum computing, and condensed matter physics.

Quantize large language models to 4-bit with minimal accuracy loss using GPTQ, enabling deployment of 70B+ models on consumer GPUs with 4× memory reduction and 3-4× faster inference.

Quantum mechanics simulations and analysis using QuTiP (Quantum Toolbox in Python). Use when working with quantum systems including: (1) quantum states (kets, bras, density matrices), (2) quantum operators and gates, (3) time evolution and dynamics (Schrödinger, master equations, Monte Carlo), (4) open quantum systems with dissipation, (5) quantum measurements and entanglement, (6) visualization (Bloch sphere, Wigner functions), (7) steady states and correlation functions, or (8) advanced methods (Floquet theory, HEOM, stochastic solvers). Handles both closed and open quantum systems across various domains including quantum optics, quantum computing, and condensed matter physics.

Quantum computing framework for building, simulating, optimizing, and executing quantum circuits. Use this skill when working with quantum algorithms, quantum circuit design, quantum simulation (noiseless or noisy), running on quantum hardware (Google, IonQ, AQT, Pasqal), circuit optimization and compilation, noise modeling and characterization, or quantum experiments and benchmarking (VQE, QAOA, QPE, randomized benchmarking).

Access Quotient market intelligence via API key or x402 micropayments, with explicit payment challenge handling.

Sets up MQTT brokers and clients for messaging in IoT systems. Use for lightweight messaging in IoT.

Analyze URLs or text to discover ranked Polymarket, Hyperliquid, and Deribit markets with Quotient edge scores, paid via on-chain x402 settlement.

Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.

Converts X (Twitter) tweets, threads, and articles to markdown with YAML front matter using a reverse-engineered API.

xUnit.net testing framework with Fact, Theory, fixtures, DI, and mocking with Moq and NSubstitute. Covers .NET testing best practices. USE WHEN: user mentions "xUnit", ".NET testing", "Fact", "Theory", "InlineData", "Moq", "NSubstitute", "C# unit test" DO NOT USE FOR: NUnit - use `nunit`, Vitest - use `vitest`, Jest - use `jest`, Playwright - use `playwright`

Maps the Salesforce CPQ managed-package object graph (SBQQ__ namespace) and explains when to use the CPQ Quote API for programmatic writes instead of direct DML.

Use when user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models (\"blockrun\", \"use grok\", \"use gpt\", \"da...

X/Twitter API integration for posting tweets, threads, reading timelines, search, and analytics. Covers OAuth auth patterns, rate limits, and platform-native content posting. Use when the user wants to interact with X programmatically.

Automates end-to-end QA: starts the app, exercises screens and API endpoints, verifies functionality and design quality, runs domain analysis, and fixes issues found.

Quantize large language models to 4-bit precision using activation-aware weight quantization, reducing memory footprint and speeding up inference with minimal accuracy loss.

Post to X (Twitter) using the official API with OAuth 1.0a. Use when you need to tweet, post updates, or publish content. Bypasses rate limits and bot detection that affect cookie-based approaches like bird CLI.

Quarkus 3.x LTS 测试驱动开发——JUnit 5、Mockito、REST Assured、Camel 测试及覆盖率

KV cache compression for LLM inference — 4.4x compression, 2x context capacity, near-lossless quality. ICLR 2026 paper implementation with vLLM integration.